Project Proposal (PDF) - Oxford Brookes University

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FP7-ICT-2011-9 STREP proposal 18/01/12 v1 [Dynact] synthetic and real data and relevant publications in AI/Imprecise Probability venues. M3 – Dissimilarity measures b/w generative models both induced by credal sets and learned from the training set. Achieved in month 18. Measured in terms of both a library of routines in Matlab and C++ running and validated in real data, and publications in AI/Computer Vision venues. M4 – Theory of classification of imprecise/precise generative models. Achieved in month 30. Measured in terms of a running library of Matlab/C++ routines implementing the different approaches to the problem (structured learning, k-NN, compressed SVM), made available to the public, and high impact publications in Machine Learning/ Vision jorunals and conferences. M5 – Learning of discriminative action parts via MIL. Achieved in month 18. Measured by software libraries running and validated on real data, publications in first class vision/ML conference and journals. M6 – Learning and classification of structured discriminative models. Achieved in month 30. Measured by software libraries running and validated on real data, available to the public, and publications in first class vision/ML conference and journals. M7 – Dataset generation. Achieved in month 12. Extensive proprietary databases in different modalities such as monocular, synchronised and range cameras will be made public, via a dedicated web site. M8 – State-of-the-art feature selection and extraction. Achieved in month 18. Measured in terms of a running library of Matlab/C++ routines implementing feature selections and extraction procedures in all modalities (monocular/spatio-temporal, stereo and range), tested in all scenarios with state-of-the-art results. M9 – All purpose action recognition framework. Achieved in month 36. At project completion a toolbox collecting the routines implementing the different stages of the all-purpose action and activity recognition framework developed here will be made public in order to maximise the impact of this work. M10 – Validation in all scenarios. Achieved in month 30. The framework and each individual component will be validated in all the relevant scenarios via thorough tests on all the public and proprietary databases. Success will be measured in terms of new state-of-the-art results on all the benchmark test-beds. (i) Overall strategy of the work plan Our workplan for the project is articulated into three, roughly parallel pipelines (see the PERT diagram of Section (v)). This is a natural consequence of the different tasks involved in delivering a robust action/activity recognition framework and prototype, in the variety of scenarios described above: 1- selecting and extracting robust features from video sequences in different modalities; 2- developing a coherent inference theory for imprecise-probabilistic graphical models; 3- working out adaptive ways of classifying dynamical generative models 4- introducing dynamics in state-of-the-art discriminative models. The first area concerns the analysis of image sequences or the related spatio-temporal volumes, required to convert the video sequences into numerical information to be processed by the algorithms (WP4). The second one encompasses the theoretical research focused on the development of the necessary learning and inference algorithms for the imprecise dynamic probabilistic graphical models we employ to describe actions and gestures (WP1), and the study the problem of classifying such complex objects in order to recognize actions, gestures or identities (WP2). Finally, WP3 is all about the development of novel dynamical discriminative models designed explicitly to represent and classify temporal patterns. There is an obvious temporal relationship between workpackages 1, 2, 3 and 4, while the results of each pipeline are to be fed to the core of the project, the Integration and Validation work package WP5. The level of modularisation of the workload is designed to allow the five partners to work efficiently during the same period on the project, with limited risk of overlap or downtime. All three pipelines are supposed to start from month 1, and run in parallel, managed by different groups. In fact, the “classification” work package (WP2) partially depends on the results of the “imprecise inference” one (WP1), but it is also autonomous in the sense that it will start by studying the problem of classifying more “classical”, precise dynamical generative models to later move to the imprecise case. Feedbacks between “Integration and Testing” (WP5) and each of the other work packages will take place throughout the duration of the whole project: initial approaches and angles on the separate tasks will have to be revised in the light of the results obtained by the demonstrator(s). These feedback loops will run for the entire second half of the project. The number of research work packages (5) is, we believe, appropriate for a project this scale. However, as it can be noticed from our previous description of the individual work packages, each WP is accurately detailed and broken down into tightly focussed tasks and sub-tasks. This thanks to the fact that the consortium already possesses extensive expertise in all the tasks involved, allowing us to plan in much detail the proposed effort, facilitating in this way the monitoring by the Commission. The milestones/control points for the project have been discussed in Section 1.3.4, and are summarised in the Table at page 27. <strong>Proposal</strong> Part B: page [22] of [67]
FP7-ICT-2011-9 STREP proposal 18/01/12 v1 [Dynact] (ii) Timing of the work packages (WPs) The project is intended to cover a period of three years. The Gantt chart below depicts the overall schedule, including the timing of the different work packages. Year 1 Year 2 Year 3 2m per I II III IV V VI I II III IV V VI I II III IV V VI WP1 WP2 WP3 WP4 WP5 WP6 The tables below are meant to give a more detailed description of the partecipation of each partner to each workpackage, stressing the contribution of each individual member of staff to the WPs. Each entry describes to which work package each person is assigned, for each two-month period in the lifetime of the project. OBU Year 1 Year 2 Year 3 I II III IV V VI I II III IV V VI I II III IV V VI PostDoc WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP5 WP5 WP5 WP5 WP5 WP5 PostDoc WP3 WP3 WP3 WP3 WP3 WP3 WP3 WP3 WP3 WP3 WP3 WP3 WP3 WP3 WP3 WP3 WP3 WP3 PostGrad WP4 WP4 WP4 WP4 WP4 WP4 WP4 WP4 WP4 WP5 WP5 WP5 WP5 WP5 WP5 WP5 WP5 WP5 Manager WP6 WP6 WP6 WP6 WP6 WP6 WP6 WP6 WP6 WP6 WP6 WP6 WP6 WP6 WP6 WP6 WP6 WP6 Coord. WP2 WP2 WP2 WP2 WP6 WP6 WP3 WP3 WP3 WP6 WP6 WP6 WP3 WP3 WP3 WP6 WP6 WP6 IDSIA Year 1 Year 2 Year 3 I II III IV V VI I II III IV V VI I II III IV V VI PostDoc1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 PostGrad WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 WP2 SYSTeMS Year 1 Year 2 Year 3 I II III IV V VI I II III IV V VI I II III IV V VI PostDoc1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 WP1 PostDoc2 WP2 WP2 WP2 WP2 WP2 WP1 WP1 WP1 WP1 SUP Year 1 Year 2 Year 3 I II III IV V VI I II III IV V VI I II III IV V VI PostGrad WP4 WP4 WP4 WP4 WP4 WP4 WP4 WP4 WP4 WP5 WP5 WP5 DYN Year 1 Year 2 Year 3 I II III IV V VI I II III IV V VI I II III IV V VI PostGrad WP4 WP4 WP4 WP5 WP5 WP5 WP5 WP5 WP5 WP5 WP5 WP5 WP5 WP5 WP5 WP5 WP5 WP5 <strong>Proposal</strong> Part B: page [23] of [67]
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